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Role of Slit2 in PV neuron Development
No full textParvalbumin expressing interneurons (PV INs) are found in the dentate gyrus of the hippocampus, a region of the brain responsible for learning, memory, and navigation. PV INs are of paramount importance in regulating circuit function, such as controlling neuronal firing and circuit synchronicity. Additionally, PV INs are necessary for creating and maintaining gamma oscillation in the circuit. Alterations of PV IN connectivity have been linked to the pathophysiology of neurological diseases such as Schizophrenia and Alzheimer’s. Moreover, we know very little about the molecular mechanism that regulate PV INs connectivity. Previous studies of PV INs molecular makeups using Ribonucleic acid sequencing (RNA seq) shows that Slit2 transcripts are enriched in these cells. Although it has previously been shown that Slit2 protein is essential for neuronal migration, axon guidance and recently, excitatory synapse formation, little is known about how it affects PV INs development. In this work we aim to unravel whether Slit2 is important for inhibitory (PV INs) development in the Dentate Gyrus of the mouse hippocampus. We hypothesize that Slit2 is involved in regulating PV INs development, and synapse formation. To investigate this hypothesis, we used genetic and confocal techniques to determine how Slit2 deletion in young adolescent animals affects PV IN morphologies and synaptic connections. We have found that knocking out Slit2 has a slight effect on PV dendrites morphology. PV INs of Slit2 mutants have a smaller shell in the middle molecular layer of the hippocampus compared to controls, signifying a smaller projection in space. Moreover, there is a slight increase of dendritic spines in the mutants. Furthermore, knocking out Slit2 increases the number of inhibitory inputs on PV INs mutants. Overall, we found Slit2 plays a role in regulating PV INs connectivity in young adolescent animals. Especially, inhibitory synapse formation on PV INs’ dendrites
2023 Midwest Peer Exchange on Balanced Mix Design (BMD): Outcomes Summary
No full textSix States from the Midwest U.S. gathered for a peer exchange and discussion on implementation activities to support Balanced Mix Design (BMD). The peer exchange was sponsored by the Federal Highway Administration (FHWA). The six States met to assess the state-of-practice for the technology, tools, and techniques in designing, verifying, and accepting asphalt mixtures for different layers within the flexible pavement structure, as well as for overlays of different pavements following BMD emerging practices. The peer exchange was held in Schaumburg, Illinois. This summary report focuses on agency motivations for considering BMD, the role of sustainability in BMD practice, implementation challenges, key takeaways, and emerging themes
PTSD Symptom Clusters Among People of Color
Get PDFAs the U.S. has grown increasingly diverse, with people of color now comprising over 40% of the population, understanding how Post-Traumatic Stress Disorder (PTSD) impacts different ethnic groups is crucial. PTSD is a debilitating condition that emerges after traumatic events, affecting individuals' daily lives and overall well-being. While previous research has examined PTSD prevalence rates across ethnicities and trauma types, there is a significant gap in understanding if and how specific PTSD symptom clusters vary among different ethnic groups. This study aimed to fill this gap. Data was collected via Prolific and the psychology subject pool. Analyzing data from 72 participants with probable PTSD, the study found varying prevalence rates of PTSD across ethnic groups although we were not sufficiently powered to examine differences across ethnic subgroups. Differences in symptom clusters across ethnic groups were not statistically significant. These findings highlight common trauma responses across ethnic groups
Analysis of Failed SSH Attempts for Intrusion Detection
Get PDFSSH brute force attacks remain among the most common attack types in computer systems. Recent threat analysis reports consistently highlight their prevalence as a top web security vulnerability. Various passive and active methodologies have been developed to deal with this problem, each with its unique set of advantages and disadvantages. Amongst all, analysis of monitoring logs is important to understand the root cause of the problem and implementing necessary countermeasures. Hence, this thesis focus on implementing automated intrusion detection solutions by analyzing historical failed SSH attempts. The data is captured between March 2022 and June 2022 from a server located at University of Nevada, Reno (UNR) campus. We first present thorough analysis of the dataset understand common patterns in the dataset such as origin of IP addresses, usernames, and time of SSH attempts. We identified various types of attack patterns, including slow, steady, and stealthy ones. Since the logs contain both benign and malicious attempts, we utilized external databases (e.g., IPWHOIS and ABUSEIPDB) to classify them as malicious or not, which served as a training data for machine learning models. We developed several machine learning models to categorize SSH attempts as malicious or benign. The models relied on several features including username, time difference of the attacks, the number of previous attempts, and similarity of IP addresses. We trained Random Forest, Decision Tree, XGBoost, SVM, and Logistic Regression models to evaluate their performance. The Decision Tree model exhibited the best performance, achieving 100% precision and a recall rate of 97.9%. In comparison, the best performed rule-based formulation failed to identify 1.5% malicious IPs whereas the Decision Tree model only missed 0.01%. We also validated the results against the public datasets. We noticed that the proposed model detected five malicious IP addresses before they appear in public databases such as ABUSEIPDB, which is a promising result for the proposed model
Improving School Improvement: Examining Coordination, Collaboration, and Learning During State Implementation of the Every Student Succeeds Act
No full textThe implementation of public policy increasingly occurs within complex, multilevel governance systems that are constrained by limited administrative capacity and resources. Consequently, it is essential to optimize the design of multilevel governance arrangements to ensure that policy implementation outcomes are aligned with established policy goals. This dissertation investigates whether and how multilevel governance arrangements can be designed to accommodate contextual characteristics and encourage critical governance process outcomes (i.e., coordination, collaboration, and collective learning) during the state implementation of school improvement processes. School improvement processes are required under the Every Student Succeeds Act (ESSA), which is the primary federal law that governs K-12 education in the United States. Under ESSA, the lowest performing schools in each state are identified using data from accountability systems to participate in improvement processes. During these processes, state education agencies (SEA), school districts, schools, and other local stakeholders are tasked with collaboratively developing and implementing school improvement plans using research-based evidence and data from the accountability system. While implementing ESSA, SEAs vary in how they structure the implementation process, specifically regarding the degree to which the process is centralized at the state-level, which may have important implications for policy outcomes. Using a mixed-method, comparative case study of school improvement processes in two U.S. states, this dissertation investigates how variation in state implementation approach fosters or inhibits policy implementation. The results indicate that a state's implementation approach impacts coordination by structuring how different levels of government interact, share information, and influence policy, and suggest how multilevel governance arrangements can be designed to balance trade-offs in centralization and the delegation of authority across governance systems during policy implementation (Chapter 2). The results also demonstrate that during policy implementation, formal administrative mechanisms can be intentionally designed to foster and reinforce critical social dynamics that serve as the foundation for ongoing interorganizational collaboration (Chapter 3). Lastly, findings suggest that the substantive activities of policies drive the emergence of information and technological resources and tools that increase information access and facilitate the use of information to promote collective learning, and can be modified to accommodate local contextual characteristics and embody local values (Chapter 4). The findings contribute to the theoretical understanding of policy implementation in complex multilevel governance systems and provide practical recommendations for improvements in education governance
Instruction Finetuning Foundation Models, Three-Stage Bubble Analysis, and Examining the Size Effect
No full textMacroeconomic indicators and financial news are important to financial professionals and market participants due to their importance in sentiment analysis, speculative bubble analysis, and portfolio selection. According to the Efficient Market Hypothesis, asset prices incorporate all available information. Within this context, information pertains to company statements, business reports, and headlines in financial news. Hence, classifying information as negative, neutral, or positive is paramount to investment decision making, portfolio selection, and detecting early warning signals for financial collapse. However, sentiment analysis in finance is quite challenging due to the "closed source" of labeled data. To overcome this, we leverage existing data sources with data generated by a large language model (through fine-tuning and prompting) and use the datasets to fine-tune another large language model for text classification in finance. We examine the impact of macroeconomic indicators and financial news in predicting speculative bubbles in a multilabel classification using ensemble methods, leveraging the fine-tuned model for text classification. We also explore how economic indicators such as dividend yield and interest rates guide portfolio selection and explain the size effect
Physical Activity in WCSD Public Elementary Schools at Different Socioeconomic Levels With Semi-Structured Recess
No full textObesity and related chronic diseases have become more prevalent in children over recent decades, with children from low socioeconomic status (SES) families being disproportionately impacted. Physical activity (PA) has been shown to help weight maintenance and reduce symptoms of obesity-related diseases and establish healthy exercise habits. It is recommended that children engage in at least 60 minutes of moderate to vigorous PA or 12,000 steps each day. However, only 24% of children meet PA guidelines. Children with low SES have more sedentary behavior and less PA than those from high SES. Boys may also achieve up to 19% more moderate-to-vigorous PA daily than girls. This indicates the need for PA interventions that can be broadly applied and are accessible and enjoyable for children from all demographics. Schools are a favorable setting for incorporating PA programs because of their controlled environment. However, many schools don't require a Physical Education (PE) curriculum which leaves recess as the only opportunity for children to exercise during the school day. Semi-structured recess is an intervention that allows children to choose from a set list of activities to participate in. It has been used as an intervention to increase the amount of PA that children receive in school and shows promise for institutions that may not have the resources to provide PE or an abundance of playground equipment for recess. Purpose: This study seeks to examine the amount of steps and vigorous PA that children receive during recess based on their school SES and gender. Additionally, this study aims to determine if semi-structured recess can increase the number of steps and vigorous PA that children get during recess. Methods: This study included 87 participants in third, fourth, and fifth grades from a low SES school (n = 44 boys, 43 girls) and 61 participants from a high SES school (n = 32 boys, 29 girls). Participants wore Yamax DigiWalker SW-200 pedometers for the duration of this study. Unstructured recess was recorded for five school days, in which participants participated in normal recess, without any intervention or instruction on activities to engage. Following this, semi-structured recess was facilitated for five days, in which participants were given a choice between several different activities to participate in. SOPLAY was used to track trends in sedentary, walking and vigorous PA. Data were analyzed using a Multivariate Analysis of Variance (MANOVA) test. Results: During unstructured recess, participants at the high SES school and low SES school had step rates of 67.3 steps per minute and 61.5 steps per minute respectively. With semi-structured recess, average step rates increases to 83.3 steps per minute and 77.3 steps per minute for the high and low SES schools. The low SES school had a significantly greater increase in step count with semi-structured recess (p < 0.001). During both unstructured and semi-structured recess, boys had higher step counts than the girls (p < 0.001). During semi-structured recess, the average number of steps between both genders and schools increased by an average of 302 steps (p < 0.001) and had a greater magnitude of change at the low SES school. Conclusion: Semi-structured recess is an intervention that can be applied to elementary schools to increase the amount of PA that children get during the school day regardless of school SES. Semi-structured recess is relatively low in cost and effort to facilitate, meaning that it may be especially beneficial to be applied in schools that lack the resources to provide a PE curriculum. More studies should be done to ensure that findings can be generalized to larger populations
Advancing Design and Detailing of Axial UHPC Columns for Wide-Range of Mixtures and Construction Types
No full textUltra-high performance concrete (UHPC) shares common constituents with normal strength concrete (NSC), such as cement, water, fine aggregates (sand), steel fibers, and admixtures. However, unlike NSC, UHPC typically excludes coarse aggregates. The inclusion of steel fibers is a crucial element in UHPC, enhancing its tensile strength (approximately two time higher when compared to NSC) and effectively bridging microcracks, providing micro-level confinement. Additionally, UHPC may incorporate carbon nanofibers for nanoconfinement, further refining its nanostructure. Despite its numerous advantages and growing markets for larger UHPC applications, a comprehensive understanding of the behavior of complete UHPC structural components, especially columns, is lacking. This knowledge gap impedes the establishment of design codes and standards for UHPC. Therefore, the goal of this doctoral research is to significantly fill this gap by contributing comprehensive insight into the axial behavior of UHPC columns of a wide-range of mixtures as well as different construction techniques, and in turn, provide, for the first time, axial design and detailing guidelines for future UHPC columns. As such, the outcome of this doctoral work promotes the use of robust UHPC materials as integral part of full structural components and systems at large through either revisiting existing or developing new UHPC sensible design tools. To further generalize such tools, the focus of this work spans both well-established commercial UHPC technologies as well as emerging variants, including carbon nanofiber (CNF)-reinforced UHPC and economically viable UHPC mixtures that utilizing locally sourced materials. In order to properly fill the identified knowledge gap and achieve the overarching goal of this doctoral study, the following specific research objectives are defined and addressed in this study: (1) establish fundamental understanding of material behavior of emerging UHPC mixtures with focus on experimental and analytical assessment of unconfined and confined behavior of CNF-enhanced UHPC cylinders; (2) investigate the axial compressive behavior of 18 large- or full-scale UHPC building columns of four different UHPC mixtures to generalize behavior trends and understanding considering various design parameters; (3) demonstrate production-scale UHPC mixing at actual precast plant by fabricating and testing four full precast circular UHPC bridge columns with varying spirals and hoops confinement; (4) leverage all tested cylinders and columns data to assess code-based and existing modulus of elasticity (MOE) prediction equations and propose new modifications for UHPC, and (5) develop general design and detailing guidelines for axial UHPC columns using a comprehensive database of the tested columns and others available in the literature, with focus on revisiting the ACI-based capacity design equation and transverse reinforcement requirements for axial UHPC columns. A mostly-experimental approach was complemented with empirical analytical approach to address the research objectives. The extensive experimental campaign employed in this study involved the fabrication and testing of hundreds of UHPC cylinders and 22 full-scale columns under axial loading. In the first part of this study, the focus was detailed behavior analysis at both material and structural levels and enriching the literature with unique and exclusive datasets towards establishing comprehensive UHPC structural databases in the future. The second part of the study leveraged all tests data, along with extended database based on current literature, to assess behavior trends and existing design tools. To be specific, this part of the study was concerned with understanding transverse reinforcement detailing and confinement on axial behavior of UHPC columns to develop UHPC sensible design guidelines. To generalize the results of this doctoral study and facilitate immediate implementation, all experimental tests and analytical assessments considered different UHPC mixtures along large number of other design variables such as transverse and longitudinal reinforcement ratios (spacing, bar diameter, and configuration), steel fiber percentage (1% versus 2% by volume), production methods (small scale in a lab environment versus large scale in precast plants), and columns geometry and cross-sections area (square, rectangular, and circular). Accordingly, the developed understanding and design guidance is sought to widen and deepen the knowledge body of UHPC columns, and directly contribute to the development of future design specifications, codes, and standards for future structural applications of UHPC
Maritime Dynamic Resource Allocation and Risk Minimization using Visual Analytics and Elitist Multi-Objective Optimization
No full textEnhancing the safety of protected regions around Navy vessels is one of the most challenging research topics in maritime domains. Robust tactical resource allocation depends on understanding of how the placements, configurations, orientations of multiple assets affect both the area and intensity of coverage around the ships. Towards this end, we built a unique resource allocation problem where we apply a randomized genetic algorithm for searching through a space of 2144 possible parameters representing area coverage and orientation of 6 tactical assets. Our elitist genetic algorithm yielded a maximum fitness value of 90%, 98%, 100% within 50, 150 and 300 generations respectively. Moreover, we put forward a distinctive constrained dynamic resource allocation problem specific to USS Arleigh Burke Destroyer model (DDG-51), where the assets are defenses and coastal guards having binoculars. To solve this, we have used a cross-generational elitist selection based evolutionary algorithm (EA) where our objective is to maximize area of coverage and minimize risksimultaneously. It is a non-deterministic polynomial-time hard (NP-Hard) problem which required searching through a space of 248 parameters and resulted in a fitness value of 98% within 35 generations. Furthermore, we present two novel visualization techniques addressing both types of resource allocations
Using an Adaptive Learning Platform to Promote Underprepared Students' Success in Corequisite Mathematics Courses: A Logistic Regression Analysis
Get PDFThe issue of college readiness persists in higher education, with many students entering college unprepared for the demands of college-level coursework. This challenge is particularly pronounced in math-intensive fields, where students frequently encounter struggles in corequisite math courses. The problem statement asserts that underprepared students, lacking essential math skills and knowledge and requiring varying levels of remediation, need personalized instruction and support to ensure their success in corequisite math courses. This study investigates whether an adaptive learning platform (EdReady) promotes the success of underprepared students in corequisite math courses. Through a two-sample proportion test comparing the proportion of students passing corequisite math courses between the treatment group (utilizing EdReady) and the control group (not using EdReady), the data analysis reveals a significant difference. More importantly, logistic regression analysis in the study demonstrates that the use of EdReady and students' prior math experience in Arithmetic are significant predictors of passing corequisite math courses. The findings of this study carry substantial implications for the design of targeted interventions and support systems aimed at enhancing the academic outcomes of underprepared students in math-intensive fields. By exploring the differentiation of passing rates and the relationship between the utilization of adaptive learning platforms and student success in their corequisite math courses, this study contributes to the ongoing dialogue on innovative strategies for supporting underprepared students in higher education